Book Image

HBase Administration Cookbook

By : Yifeng Jiang
Book Image

HBase Administration Cookbook

By: Yifeng Jiang

Overview of this book

As an Open Source distributed big data store, HBase scales to billions of rows, with millions of columns and sits on top of the clusters of commodity machines. If you are looking for a way to store and access a huge amount of data in real-time, then look no further than HBase.HBase Administration Cookbook provides practical examples and simple step-by-step instructions for you to administrate HBase with ease. The recipes cover a wide range of processes for managing a fully distributed, highly available HBase cluster on the cloud. Working with such a huge amount of data means that an organized and manageable process is key and this book will help you to achieve that.The recipes in this practical cookbook start from setting up a fully distributed HBase cluster and moving data into it. You will learn how to use all of the tools for day-to-day administration tasks as well as for efficiently managing and monitoring the cluster to achieve the best performance possible. Understanding the relationship between Hadoop and HBase will allow you to get the best out of HBase so the book will show you how to set up Hadoop clusters, configure Hadoop to cooperate with HBase, and tune its performance.
Table of Contents (16 chapters)
HBase Administration Cookbook
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface

Introduction


It is vital to monitor the status of an HBase cluster to ensure that it is operating as expected. The challenge of monitoring a distributed system, besides taking the case of each server separately, is that you will also need to look at the overall status of the cluster.

HBase inherits its monitoring APIs from Hadoop's metrics framework. It exposes a large amount of metrics, giving the insight information of the cluster. These metrics are subsequently configured to expose other monitoring systems, such as Ganglia or OpenTSDB, to gather and make them visible through graphs. Ganglia/OpenTSDB graphs help us understand the insight of the cluster, both for a single server and the entire cluster.

Graphs are good for getting an overview of the historical status, but we also need a mechanism to check the current state of the cluster, and send us notifications or take some automatic actions if the cluster has some problem. A good solution for this kind of monitoring task is Nagios. Nagios...